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Large scale experiments to improve monopile scour protection design adapted to climate change
<p>Offshore wind farms contribute significantly to contemporary renewable energy production. By installing these offshore structures, new technical design challenges arise, such as foundation optimisation. Present LCoE (Levelized Cost of Electricity) of offshore wind turbines amounts up to 170 Euro/MWh (Crown Estate, 2015), but the ambition is to reduce this by 2020 to 90 Euro/MWh (EY, 2015). Offshore wind turbine foundation costs are 20 % of the total costs in the case of a monopile (NREL, 2014). An important part of those costs is related to the foundation's scour protection. Therefore, optimisations in the design of the scour protection are indispensable.<br>Another promising track to reduce the costs of offshore wind turbines is their lifetime extension. Recent studies (Crown Estate, 2015) show that a 5 year lifetime extension can reduce the cost per kWh by 6 %. To check the feasibility of a lifetime extension, it will be necessary to diagnose or inspect the conditions of several core parts of the turbines, notably its foundation and scour protection. Therefore, more fundamental insight into the (longer term damage) behaviour of the scour protection around the monopile is needed.<br>Beside the interest in design optimisation and lifetime extension, the influence of climate change needs to be investigated in more detail. Climate change will increase the design storm conditions and influence the scour protection stability. Therefore, research towards a risk-based design will help to evaluate the functionality of scour protection already installed and improve the design of future scour protections adapted to climate change.<br>Based on the above motivations, the main research objective is to establish a basic benchmark dataset on the stability of scour protection around monopile foundations to serve as a basis for model tests in other flumes in the future (rather than to carry out a traditional sensitivity study with a fine resolution for all governing parameters). <br>To achieve the goals, scour researchers from several institutions are set to start work on a collaborative project at HR Wallingford's Fast Flow Facility (FFF) as part of PROTEUS, an EU-funded Hydralab+ project. Hydralab+ which is funded by the EU's Horizon 2020 Research and Innovation Programme brings together facilities and researchers in experimental hydraulic and hydrodynamics.<br>The research project aims to improve the design of scour protection around offshore wind turbine monopiles, as well as future-proofing them against the impacts of climate change. <br>PROTEUS, which stands for the 'PRotection of Offshore wind Turbine monopilEs against Scouring' will facilitate the conducting of a series of large scale experiments over a seven week period in the FFF flume at HR Wallingford's UK physical modelling facilities.<br>Partners involved in PROTEUS are: Department of Civil Engineering at Ghent University, HR Wallingford (UK), the Ludwig-Franzius Institute for Hydraulic, Estuarine and Coastal Engineering at the University of Hannover, the Faculty of Engineering at the University of Porto, the Geotechnics division of the Belgian Department of Mobility and Public Works, and International Marine and Dredging Consultants (IMDC nv).</p>
Branch-scale ember generation study at Oregon State University
<p>Videos and other supporting data for project used to identify the time to generation of dowels or natural samples when burned in a vertical wind tunnel. The overall goal was to identify which physical processes are most important in controlling ignition.</p> <p> </p> <p>The data was used for the publication, Effects of fuel characteristics on ember generation characteristics at branch-scales, International Journal of Wildland fire (in press). </p>
Subgenus Lestes (15-28). L. sponsa: 15. Left side of head of ♂ showing ridge behind antennal cavity; 16. pterostigma of right forewing; 17-18. anal appendages dorsally and from left; 19. prophallus; 20. terminal segments and ovipositor sheath and vulvar scale at its base (all Germany except prophallus from Japan). L. barbarus (Morocco): 21. right anal appendages from above; 22. prophallus. L. dryas (California): 23. anal appendages dorsally, 24. prophallus. L. macrostigma (Turkey): 25, 26. the same. L. virens (Germany): 27, 28. the same. f = flange, hd = hood, li = ligula, sc = scoop, sh = shelf. in A revision of African Lestidae (Odonata) (excerpt)
Subgenus Lestes (15-28). L. sponsa: 15. Left side of head of ♂ showing ridge behind antennal cavity; 16. pterostigma of right forewing; 17-18. anal appendages dorsally and from left; 19. prophallus; 20. terminal segments and ovipositor sheath and vulvar scale at its base (all Germany except prophallus from Japan). L. barbarus (Morocco): 21. right anal appendages from above; 22. prophallus. L. dryas (California): 23. anal appendages dorsally, 24. prophallus. L. macrostigma (Turkey): 25, 26. the same. L. virens (Germany): 27, 28. the same. f = flange, hd = hood, li = ligula, sc = scoop, sh = shelf.
Industry-scale Application and Evaluation of Deep Learning for Drug Target Prediction
<p>Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine learning algorithms in computer vision, speech recognition, natural language processing and generative modelling. Recent works on publicly available pharmaceutical data showed that AI methods are highly promising for Drug Target prediction. However, the quality of public data might be different than that of industry data due to different labs reporting measurements, different measurement techniques, fewer samples and less diverse and specialized assays. As part of a European funded project (ExCAPE), that brought together expertise from pharmaceutical industry, machine learning, and high-performance computing, we investigated how well machine learning models obtained from public data can be transferred to internal pharmaceutical industry data. Our results show that machine learning models trained on public data can indeed maintain their predictive power to a large degree when applied to industry data. Moreover, we observed that deep learning derived machine learning models outperformed comparable models, which were trained by other machine learning algorithms, when applied to internal pharmaceutical company datasets. To our knowledge, this is the first large-scale study evaluating the potential of machine learning and especially deep learning directly at the level of industry-scale settings and moreover investigating the transferability of publicly learned target prediction models towards industrial bioactivity prediction pipelines.</p>
РИС. 1. Личинки мидии Mytilus galloprovincialis на стадиЯх: A – стерробластулы (стрелками обоЗначены три рЯда ресничек) и B – трохофоры (стрелкоЙ обоЗначены реснички апикального султанчика). МасШтаб: 15 мкм. FIG. 1. Larvae of the mussel Mytilus galloprovincialis at two different stages: (A) –sterroblastula (arrows indicate three rows of cilia) and (B) – trochophore (the arrow indicates cilia of the parietal plume). Scale: 15 µm. in Морфометрические особенности личинок мидии Mytilus galloprovincialis (Lamarck, 1819) (Bivalvia: Mytilidae) в онтогенеЗе
РИС. 1. Личинки мидии Mytilus galloprovincialis на стадиЯх: A – стерробластулы (стрелками обоЗначены три рЯда ресничек) и B – трохофоры (стрелкоЙ обоЗначены реснички апикального султанчика). МасШтаб: 15 мкм. FIG. 1. Larvae of the mussel Mytilus galloprovincialis at two different stages: (A) –sterroblastula (arrows indicate three rows of cilia) and (B) – trochophore (the arrow indicates cilia of the parietal plume). Scale: 15 µm.
Figure 1 in Haemagogus spegazzinii Brèthes, 1912 (Diptera: Culicidae) in Brazilian semiarid: resistance in eggs and scale color variation in adults
Figure 1 - Location of the collection area of Haemagogus spp. eggs in the semiarid region of northeastern Brazil. a) Map of Brazil, with Rio Grande do Norte state highlighted in red. b) Map of Rio Grande do Norte, highlighting the municipality of Currais Novos. c) Map of Currais Novos, highlighting the collection area. d) Collection area (Cânion dos Apertados) in the semiarid of Rio Grande do Norte, Brazil; Green points: positive ovitraps; Red points: negative ovitraps.
Fig. 2. 1–10 in Near-infrared spectroscopy and microstructure of the scales of Sabethes (Sabethes) albiprivus (Diptera: Culicidae)
Fig. 2. 1–10: Specimens with scales that reflect blue, purple and green; 11–14: Specimens with scales that reflect golden and silver. The scale bars of the dorsal view images (1, 3, 5, 7, 9, 11, 13) represents 1 mm and of the side views of the abdomen (2, 6, 8, 10, 12, 14) indicate 0.5 mm.
Fig. 1 in Near-infrared spectroscopy and microstructure of the scales of Sabethes (Sabethes) albiprivus (Diptera: Culicidae)
Fig. 1. Scanning electron micrograph of a scale on the antepronotum of Sabethes albiprivus. The rectangle indicates where the images were obtained at 10,000× magnification. Legends: ap, apex; lr, longitudinal ridge; pe, pedicel.
Figs.: 1–4. Nectarinella manauara sp. nov. (1) Head, anterior view; (2) posterior view, red arrow points to vestigial occipital carina; (3) mesosoma, dorsal view, (4) lateral view; (5) head of N. championi, posterior view, red arrow points to vestigial occipital carina; (6) head of paratype of N. xavantinensis, anterior view; approximately same scale as (5). in Nectarinella manauara, new species and record of the genus from Brazilian Amazonia (Hymenoptera, Vespidae, Polistinae)
Figs.: 1–4. Nectarinella manauara sp. nov. (1) Head, anterior view; (2) posterior view, red arrow points to vestigial occipital carina; (3) mesosoma, dorsal view, (4) lateral view; (5) head of N. championi, posterior view, red arrow points to vestigial occipital carina; (6) head of paratype of N. xavantinensis, anterior view; approximately same scale as (5).
Figure 7 in Five new records of soil scale insects (Hemiptera: Coccomorpha) for Indonesia
Figure 7. Microphotographs of Ripersiella sabahica (Williams, 2004). (A) Ventral section of head with six-segmented antennae (an) and eyespot (ey) full developed. (B) Labium. (C) Ventral abdominal segments III and IV with circulus on each one. (D) Hind leg. (E) Claw with ungual digitule setose. (F) Bitubular duct. (G) Oral collar tubular duct.
Figure 6 in Five new records of soil scale insects (Hemiptera: Coccomorpha) for Indonesia
Figure 6. Microphotographs of Ripersiella cryphia (Williams, 2004): (A) Five-segmented antenna. (B) Cephalic plate. (C) Claw with ungal digitule setose. (D) Venter of abdominal segments II and III with circulus in each segment. (E) Genital chamber. (F) Anal ring. (G) Ventral multilocular disc pores. (H) Bitubular ducts.
Figure 3 in Five new records of soil scale insects (Hemiptera: Coccomorpha) for Indonesia
Figure 3. Microphotographs of Rhizoecus americanus (Hambleton, 1946): (A) Section of head and thorax with antenna (an) and foreleg (al). (B) Section of abdomen with genital chamber (gc) and anal ring (ar). (C) Ventral section of abdomen with multilocular disc pores (mp) and tritubular ducts (st). (D) Submargin of abdomen with tritubular ducts.
Figure 8 in Five new records of soil scale insects (Hemiptera: Coccomorpha) for Indonesia
Figure 8. Taxonomic illustrations of antennae of (A) Rhizoecus pignerator (Williams, 2004), (B) Rhizoecus omphalius Williams, 2004 and (C) Ripersiella cryphia (Williams, 2004).
Figure 1 in Five new records of soil scale insects (Hemiptera: Coccomorpha) for Indonesia
Figure 1. Microphotographs of Pseudococcus saccharicola (Takahashi, 1928): (A) Eight-segmented antenna. (B) Eyespot without pores associated. (C) Hind leg with translucid pores in coxa (cx) and tibia (tb). (D) section of dorsal marginal area in abdominal segment I with oral rim tubular duct (or) near to cerarious (ce).
Fig. 2 in The Distribution of Soil Testate Amoebae under Winter Snow Cover at the Plot-scale Level in Arctic Tundra (Qeqertarsuaq/Disko Island, West Greenland)
Fig. 2. Maps of the spatial distribution of the explanatory environmental variables (A – microtopography; B – snow depth; C – loge(substrate density)) plotted against their spatial coordinates at 57 sampling locations within an 8 × 15 m plot in arctic tundra in Qeqertarsuaq/Disko Island (West Greenland). All data are centred on 0, so square sizes are proportional to the deviations from the mean values at the plot. Open symbols are used for negative values and the filled symbols are used for positive values. Spatial patterns are visualised as aggregations of similar size and colour.
Fig. 1. Zoelucasa sablensis. a in Zoelucasa sablensis n. gen. et n. sp. (Cercozoa, Incertae Sedis), a New Scale-covered Flagellate from Marine Sandy Shores
Fig. 1. Zoelucasa sablensis. a – diagrammatic representation of cellular components, where: af – anterior flagellum, tf – trailing flagellum, S – scales, N – nucleus, n – nucleolus; b – external arrangement of scales; c, d – SEM images of whole, dried cells showing covering of scales and flagella; e – DIC image of cell showing optical section of the scale layer (arrows); f – nucleus (N); g, h – nucleus (large arrow) and parallel flagellar insertion in anterior pocket (small arrows) of cells that have retracted to a posterior position within their loricae; i – trailing flagellum in a "swimming" cell; j – anterior pocket (larger arrow) and parallel emergence of two flagella (small arrows); k – diagrammatic representation of the zig-zag pattern of cell "swimming" movement; l, m – compressed cells showing the flagella (arrows) and disassociated scales around the cells (note the fractures of some scales in m); n–r – TEM images of scales.
Figure. The phylogenetic tree showing the relationship among Brevibacillus parabrevis strains SA2.2 and TJ2.3, Bacillus licheniformis MG4.2, and their phylogenetically closest type strains. The GenBank accession numbers of the type strains and studied strains are shown following species names. Distance matrix was calculated by Kimura's 2-parameter model. The scale bar indicates 0.02 substitutions per nucleotide position. Alicyclobacillus pohliae AJ564766 served as an out-group. in Distribution of extracellular enzyme-producing bacteria in the digestive tracts of 4 brackish water fish species
Figure. The phylogenetic tree showing the relationship among Brevibacillus parabrevis strains SA2.2 and TJ2.3, Bacillus licheniformis MG4.2, and their phylogenetically closest type strains. The GenBank accession numbers of the type strains and studied strains are shown following species names. Distance matrix was calculated by Kimura's 2-parameter model. The scale bar indicates 0.02 substitutions per nucleotide position. Alicyclobacillus pohliae AJ564766 served as an out-group.
Text-fig. 2. A – Elasmobranchii gen. et spec. indet. specimen NM Pc 02876b; B – Scopeloides glarisianus dentary NM Pc 02888 (the white arrows mark the tips of the "fang-like" teeth); C – S. glarisianus disarticulated skeleton NM Pc 02887a; D – Sardinella sardinites scale NM Pc 02886; E – Clupeidae gen. et spec. indet. articulated skeleton without head NM Pc 02889; F – Anenchelum glarisianum body fragment NM Pc 02880a; G – Percoidei gen. et sp. indet. preoperculum (G-1) and its interpretation (G-2) NM Pc 02891. The arrow shows the enlarged spine in the angle between rami verticalis and horizontalis. Abbreviations: cl – cleithrum; op – operculum; pcl – postcleithrum. in An Annotated List Of The Oligocene Fish Fauna From The Osíčko Locality (Menilitic Fm.; Moravia, The Czech Republic)
Text-fig. 2. A – Elasmobranchii gen. et spec. indet. specimen NM Pc 02876b; B – Scopeloides glarisianus dentary NM Pc 02888 (the white arrows mark the tips of the "fang-like" teeth); C – S. glarisianus disarticulated skeleton NM Pc 02887a; D – Sardinella sardinites scale NM Pc 02886; E – Clupeidae gen. et spec. indet. articulated skeleton without head NM Pc 02889; F – Anenchelum glarisianum body fragment NM Pc 02880a; G – Percoidei gen. et sp. indet. preoperculum (G-1) and its interpretation (G-2) NM Pc 02891. The arrow shows the enlarged spine in the angle between rami verticalis and horizontalis. Abbreviations: cl – cleithrum; op – operculum; pcl – postcleithrum.
Text-fig. 5. Reconstruction of aeduellids from the Bohemian Massif. 1 – Spinarichthys dispersus (FRITSCH, 1895) (after Štamberg 1986). 2 – Neslovicella elongata ŠTAMBERG, 2010 (after Štamberg 2010). 3 – Neslovicella rzehaki ŠTAMBERG, 2007 (after Štamberg 2007). 4 – Bourbonnella hirsuta ŠTAMBERG, 2007 (after Štamberg, 2007). Scale bar represents 20 mm. in Knowledge Of The Carboniferous And Permian Actinopterygian Fishes Of The Bohemian Massif - 100 Years After Antonín Frič
Text-fig. 5. Reconstruction of aeduellids from the Bohemian Massif. 1 – Spinarichthys dispersus (FRITSCH, 1895) (after Štamberg 1986). 2 – Neslovicella elongata ŠTAMBERG, 2010 (after Štamberg 2010). 3 – Neslovicella rzehaki ŠTAMBERG, 2007 (after Štamberg 2007). 4 – Bourbonnella hirsuta ŠTAMBERG, 2007 (after Štamberg, 2007). Scale bar represents 20 mm.
Text-fig. 2. Reconstruction of some Westphalian and Stephanian actinopterygians. Figs 1 – 5 after Štamberg (1991), Fig. 6 after Westoll (1944). Scale bars represent 20 mm. 1 – Acrolepis gigas (FRIČ, 1877), 2 – "Elonichthys" krejcii (FRITSCH, 1895), figured after the original holotype of Acrolepis sphaerosideritarum FRITSCH, 1895, 3 – "Elonichthys" krejcii (FRITSCH, 1895), figured after the original holotype of Acrolepis krejcii FRITSCH, 1895, 4 – Sphaerolepis kounoviensis FRIČ, 1877, 5 – Sceletophorus biserialis FRITSCH, 1894, 6 – Pyritocephalus sculptus (FRIČ, 1875). in Knowledge Of The Carboniferous And Permian Actinopterygian Fishes Of The Bohemian Massif - 100 Years After Antonín Frič
Text-fig. 2. Reconstruction of some Westphalian and Stephanian actinopterygians. Figs 1 – 5 after Štamberg (1991), Fig. 6 after Westoll (1944). Scale bars represent 20 mm. 1 – Acrolepis gigas (FRIČ, 1877), 2 – "Elonichthys" krejcii (FRITSCH, 1895), figured after the original holotype of Acrolepis sphaerosideritarum FRITSCH, 1895, 3 – "Elonichthys" krejcii (FRITSCH, 1895), figured after the original holotype of Acrolepis krejcii FRITSCH, 1895, 4 – Sphaerolepis kounoviensis FRIČ, 1877, 5 – Sceletophorus biserialis FRITSCH, 1894, 6 – Pyritocephalus sculptus (FRIČ, 1875).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.